In the same fashion, a skip connection is used, while \(\phi _{N(v)\rightarrow v}\)  is either identity or a linear layer followed by a non-linearity, depending on whether the graph has edge features or not. \(e_{v_j \rightarrow v_i}\)  is used to denote an edge from node \(v_j\)  to node \(v_i\) . This results in a GIN-like convolution [1]} with a skip connection:
\(v_i^t = v_i^t + f_n\left(v_i^t, \sum _{v_j^t \in N(v_i)} \phi _{N(v)\rightarrow v}\left(v_j^t, e_{v_j \rightarrow v_i}\right) \right) \quad \textbf {if} \ \left|A(v_i)\right| > 0 \ \textbf {else} \ v_i^{t} .\) 
